The above \(fbr\)  heuristic was further studied
in an influential paper [1]}.
An implementation from [2]} as a LIBLINEAR
extension has long been publicly available.
Interestingly, our survey seems to indicate that
no one in the field of representation learning ever tried it.
One reason may be that the procedure is complicated.
If we also select the parameter \(C\) , then a cumbersome
outer-level CV to sweep some \((C, fbr)\)  pairs is needed.
Furthermore, it is difficult to use the same data split,
especially in the inner CV. Another reason may be that
as a heuristic, people are not confident about the
method. For example, [3]} stated that because
“thresholding can affect the final prediction performance drastically [2]}, [5]},”
they decided that
“For evaluation purpose, we assume the number of labels of unobserved nodes is already known.”
